Identifying early language predictors: A replication of Gasparini et al. (2023) confirming applicability in a general population cohort.

BACKGROUND: Identifying language disorders earlier can help children receive the support needed to improve developmental outcomes and quality of life. Despite the prevalence and impacts of persistent language disorder, there are surprisingly no robust predictor tools available. This makes it difficult for researchers to recruit young children into early intervention trials, which in turn impedes advances in providing effective early interventions to children who need it. AIMS: To validate externally a predictor set of six variables previously identified to be predictive of language at 11 years of age, using data from the Longitudinal Study of Australian Children (LSAC) birth cohort. Also, to examine whether additional LSAC variables arose as predictive of language outcome. METHODS & PROCEDURES: A total of 5107 children were recruited to LSAC with developmental measures collected from 0 to 3 years. At 11-12 years, children completed the Clinical Evaluation of Language Fundamentals, 4th Edition, Recalling Sentences subtest. We used SuperLearner to estimate the accuracy of six previously identified parent-reported variables from ages 2-3 years in predicting low language (sentence recall score ≥ 1.5 SD below the mean) at 11-12 years. Random forests were used to identify any additional variables predictive of language outcome. OUTCOMES & RESULTS: Complete data were available for 523 participants (52.20% girls), 27 (5.16%) of whom had a low language score. The six predictors yielded fair accuracy: 78% sensitivity (95% confidence interval (CI) = [58, 91]) and 71% specificity (95% CI = [67, 75]). These predictors relate to sentence complexity, vocabulary and behaviour. The random forests analysis identified similar predictors. CONCLUSIONS & IMPLICATIONS: We identified an ultra-short set of variables that predicts 11-12-year language outcome with 'fair' accuracy. In one of few replication studies of this scale in the field, these methods have now been conducted across two population-based cohorts, with consistent results. An imminent practical implication of these findings is using these predictors to aid recruitment into early language intervention studies. Future research can continue to refine the accuracy of early predictors to work towards earlier identification in a clinical context. WHAT THIS PAPER ADDS: What is already known on the subject There are no robust predictor sets of child language disorder despite its prevalence and far-reaching impacts. A previous study identified six variables collected at age 2-3 years that predicted 11-12-year language with 75% sensitivity and 81% specificity, which warranted replication in a separate cohort. What this study adds to the existing knowledge We used machine learning methods to identify a set of six questions asked at age 2-3 years with ≥ 71% sensitivity and specificity for predicting low language outcome at 11-12 years, now showing consistent results across two large-scale population-based cohort studies. What are the potential or clinical implications of this work? This predictor set is more accurate than existing feasible methods and can be translated into a low-resource and time-efficient recruitment tool for early language intervention studies, leading to improved clinical service provision for young children likely to have persisting language difficulties.

Diagnostic performance of the CellaVision preclassification neutrophil count - time to bypass the reclassification?

OBJECTIVES: The objective of this study was to perform a method comparison between the CellaVision preclassification neutrophil count and the reclassification neutrophil count performed by trained laboratory technicians, and to evaluate the diagnostic performance of the preclassification neutrophil count at clinical decision levels. METHODS: We retrospectively identified patient samples through 2019-2022 in which the differential count was performed on Cellavision (n = 4,354). Data on sample characteristics and leukocyte- and differential counts was extracted from the electronic medical journal. For each sample, data containing the pre- and reclassification leukocyte classification, respectively, was extracted from the Cellavision software. Method comparison between the pre-and reclassification neutrophil count was performed using Bland Altman analysis. Diagnostic performance of the preclassification neutrophil count was evaluated according to four pre-specified categories of results with the reclassification as reference method. RESULTS: The median difference between the pre- and reclassification neutrophil count was 0.044 x 109/L. The preclassification neutrophil count categorised 95.6% of all samples correctly according to the four categories. The sensitivity, specificity, positive predictive value and negative predictive value for detecting neutrophilia > 7.00 x 109/L was 98.8%, 97.2%, 95.8%, and 99.2%, respectively. In samples with leukopenia (n = 543), the sensitivity, specificity, positive predictive value and negative predictive value for detecting severe neutropenia (< 0.50 x 109/L) was 97.7%, 99.1%, 98.6%, and 98.5%, respectively. CONCLUSION: The diagnostic performance of the CellaVision preclassification neutrophil count was satisfactory. The preclassification neutrophil count may be released to the electronic medical journal to improve turnaround time and benefit laboratory management.

Sample size calculation for data reliability and diagnostic performance: a go-to review.

Sample size, namely the number of subjects that should be included in a study to reach the desired endpoint and statistical power, is a fundamental concept of scientific research. Indeed, sample size must be planned a priori, and tailored to the main endpoint of the study, to avoid including too many subjects, thus possibly exposing them to additional risks while also wasting time and resources, or too few subjects, failing to reach the desired purpose. We offer a simple, go-to review of methods for sample size calculation for studies concerning data reliability (repeatability/reproducibility) and diagnostic performance. For studies concerning data reliability, we considered Cohen's κ or intraclass correlation coefficient (ICC) for hypothesis testing, estimation of Cohen's κ or ICC, and Bland-Altman analyses. With regards to diagnostic performance, we considered accuracy or sensitivity/specificity versus reference standards, the comparison of diagnostic performances, and the comparisons of areas under the receiver operating characteristics curve. Finally, we considered the special cases of dropouts or retrospective case exclusions, multiple endpoints, lack of prior data estimates, and the selection of unusual thresholds for α and ß errors. For the most frequent cases, we provide example of software freely available on the Internet.Relevance statement Sample size calculation is a fundamental factor influencing the quality of studies on repeatability/reproducibility and diagnostic performance in radiology.Key points• Sample size is a concept related to precision and statistical power.• It has ethical implications, especially when patients are exposed to risks.• Sample size should always be calculated before starting a study.• This review offers simple, go-to methods for sample size calculations.

Comparative evaluation of screening tools for sarcopenia in patients with axial spondyloarthritis.

Sarcopenia is linked to chronic inflammation and muscle wasting. This research aims to compare the screening accuracy of tools for sarcopenia in axial spondyloarthritis (axSpA). A cross-sectional study involving 104 axSpA patients was conducted at Phramongkutklao Hospital between January 2020 and February 2021. Sarcopenia was diagnosed according to the AWGS 2019 criteria. Appendicular skeletal muscle mass was measured using DXA. SARC-F, SARC-CalF, and SARC-F+EBM, muscle strength, and physical performance were assessed. The screening tests were evaluated using ROC curves. The optimal cutoffs were identified with the Youden index. Most patients were male (74%), with a mean (SD) age and disease duration of 42.6 (12.22) and 8.3 (8.5), respectively. The prevalence of sarcopenia was 22.1%. The AUCs (95% CI) for calf circumference, SARC-F, SARC-CalF, SARC-F+EBM, handgrip strength, chair stand time, gait speed, and time and go test were 0.830 (0.734, 0.925), 0.509 (0.373-0.645), 0.782 (0.670-0.894), 0.856 (0.758-0.954), 0.710 (0.594-0.825), 0.640 (0.508-0.772), 0.689 (0.539-0.839), and 0.711 (0.576-0.846), respectively. The optimal cutoffs for SARC-F, SARC-CalF, and SARC-F+EBM were 1, 10, and 10, with sensitivity/specificity of 81.0%/29.7%, 90.5%/68.9%, and 77.3%/87.2%, respectively. Calf circumference, SARC-CalF, and SARC-F+EBM had the best performance to screen for sarcopenia in axSpA patients. Lowering the thresholds would potentially enhance the performances of SARC-CalF and SARC-F+EBM.

Robust AI-Driven Segmentation of Glioblastoma T1c and FLAIR MRI Series and the Low Variability of the MRIMath© Smart Manual Contouring Platform.

Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen-Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists' scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists' ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists' scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists' scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland-Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform's low inter-user variability and the high accuracy of its T1c and FLAIR AI models.

Excellent accuracy of magnetic resonance imaging for diagnosis of discoid meniscus tears: A systematic review and meta-analysis.

Purpose: The discoid meniscus (DM) is distinguished by its thickened, disc-shaped formation, which extends over the tibial plateau. The likelihood of developing osteoarthritis escalates if a DM tear remains undiagnosed and untreated. While DM tears can be diagnosed through arthroscopy, the high cost, invasive nature and limited availability of this procedure highlight the need for a better diagnostic modality. This study aims to determine the accuracy of magnetic resonance imaging (MRI) in diagnosing DM tears. Methods: A systematic review was conducted to gather articles with at least 10 cases on the comparison of MRI and arthroscopy as the gold standard for DM tear diagnosis. Stata and MetaDisc were used to conduct the statistical analysis. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results: Five diagnostic performance studies, derived from four original research papers involving 305 patients, were evaluated. Based on the pooled data, the sensitivity, specificity, diagnostic odds ratio, positive limit of detection and negative limit of detection were found to be 0.87 (95% confidence interval [CI], 0.82-0.91) and 0.84 (95% CI, 0.75-0.90), 32.88 (95% CI, 5.81-186.02), 5.22 (95% CI, 1.71-15.92) and 0.18 (95% CI, 0.09-0.38), respectively. A hierarchical summary receiver operating characteristic curve with an area under the curve of 0.92 was generated. Conclusion: This meta-analysis demonstrates that MRI has excellent sensitivity and specificity for diagnosing DM tears. Despite its lower accuracy compared to arthroscopy, MRI can be used in symptomatic patients as a viable alternative to arthroscopy due to its inherent advantages. Level of Evidence: Level IV.

Ocular Signs and Testing Most Compatible with Sarcoidosis-Associated Uveitis: A Latent Class Analysis.

Purpose: This study aims to explore the potential subgroups of sarcoidosis-associated uveitis (SAU) within a multicenter cohort of uveitis participants. Design: Cross-sectional study. Participants: A cohort of 826 uveitis patients from a uveitis registry from 19 clinical centers in 12 countries between January 2011 and April 2015. Methods: We employed a latent class analysis (LCA) incorporating recommended tests and clinical signs from the revised International Workshop on Ocular Sarcoidosis (IWOS) to identify potential SAU subgroups within the multicenter uveitis cohort. Additionally, we assessed the performance of the individual tests and clinical signs in classifying the potential subclasses. Main Outcome Measures: Latent subtypes of SAU. Results: Among 826 participants included in this analysis, the 2-class LCA model provided a best fit, with the lowest Bayesian information criteria of 7218.7 and an entropy of 0.715. One class, consisting of 548 participants, represented the non-SAU, whereas the second class, comprised of 278 participants, was most representative of SAU. Snowballs/string of pearls vitreous opacities had the best test performance for classification, followed by bilaterality and bilateral hilar lymphadenopathy (BHL). The combination of 4 tests with the highest classification importance, including snowballs/string of pearls vitreous opacities, periphlebitis and/or macroaneurysm, bilaterality, and BHL, demonstrated a sensitivity of 84.8% and a specificity of 95.4% in classifying the SAU subtypes. In the exploratory analysis of the 3-class LCA model, which had comparable fit indices as the 2-class model, we identified a candidate non-SAU subtype, candidate SAU subtype with pulmonary involvement, and a candidate SAU with less pulmonary involvement. Conclusions: Latent class modeling, incorporating tests and clinical signs from the revised IWOS criteria, effectively identified a subset of participants with clinical features indicative of SAU. Though the sensitivity of individual ocular signs or tests was not perfect, using a combination of tests provided a satisfactory performance in classifying the SAU subclasses identified by the 2-class LCA model. Notably, the classes identified by the 3-class LCA model, including a non-SAU subtype, an SAU subtype with pulmonary involvement, and an SAU subtype with less pulmonary involvement, may have potential implication for clinical practice, and hence should be validated in further research. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Accuracy of contrast-enhanced CT in liver neoplasms in children under 2 years age.

BACKGROUND: Multiple differentials exist for pediatric liver tumors under 2 years. Accurate imaging diagnosis may obviate the need for tissue sampling in most cases. OBJECTIVE: To evaluate the imaging features and diagnostic accuracy of computed tomography (CT) in liver tumors in children under 2 years. METHODS: Eighty-eight children under 2 years with treatment naive liver neoplasms and baseline contrast-enhanced CT were included in this institutional review board approved retrospective study. Two blinded onco-radiologists assessed these tumors in consensus. Findings assessed included enhancement pattern, lobulated appearance, cystic change, calcifications, central scar-like appearance, and metastases. The radiologists classified the lesion as hepatoblastoma, infantile hemangioma, mesenchymal hamartoma, rhabdoid tumor, or indeterminate, first based purely on imaging and then after alpha-fetoprotein (AFP) correlation. Multivariate analysis and methods of comparing means and frequencies were used for statistical analysis wherever applicable. Diagnostic accuracy, sensitivity, and positive predictive values were analyzed. RESULTS: The mean age of the sample was 11.4 months (95% CI, 10.9-11.8) with 50/88 (57%) boys. The study included 72 hepatoblastomas, 6 hemangiomas, 4 mesenchymal hamartomas, and 6 rhabdoid tumors. Presence of calcifications, multilobular pattern of arterial enhancement, lobulated morphology, and central scar-like appearance was significantly associated with hepatoblastomas (P-value < 0.05). Fourteen out of eighty-eight lesions were called indeterminate based on imaging alone; six lesions remained indeterminate after AFP correlation. Pure radiology-based diagnostic accuracy was 81.8% (95% CI, 72.2-89.2%), which increased to 92.1% (95% CI, 84.3-96.7%) (P-value > 0.05) after AFP correlation, with one hepatoblastoma misdiagnosed as a rhabdoid tumor. If indeterminate lesions were excluded for biopsy, the accuracy would be 98.8% (95% CI, 93.4-99.9%). CONCLUSION: CT had high accuracy for diagnosing liver neoplasms in the under 2-year age population after AFP correlation. Certain imaging features were significantly associated with the diagnosis of hepatoblastoma. A policy of biopsying only indeterminate lesions after CT and AFP correlation would avoid sampling in the majority of patients.

Distinguishing thymic cysts from low-risk thymomas via [18F]FDG PET/CT.

BACKGROUND: Thymic cysts are a rare benign disease that needs to be distinguished from low-risk thymoma. [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is a non-invasive imaging technique used in the differential diagnosis of thymic epithelial tumours, but its usefulness for thymic cysts remains unclear. Our study evaluated the utility of visual findings and quantitative parameters of [18F]FDG PET/CT for differentiating between thymic cysts and low-risk thymomas. METHODS: Patients who underwent preoperative [18F]FDG PET/CT followed by thymectomy for a thymic mass were retrospectively analyzed. The visual [18F]FDG PET/CT findings evaluated were PET visual grade, PET central metabolic defect, and CT shape. The quantitative [18F]FDG PET/CT parameters evaluated were PET maximum standardized uptake value (SUVmax), CT diameter (cm), and CT attenuation in Hounsfield units (HU). Findings and parameters for differentiating thymic cysts from low-risk thymomas were assessed using Pearson's chi-square test, the Mann-Whitney U-test, and receiver operating characteristics (ROC) curve analysis. RESULTS: Seventy patients (18 thymic cysts and 52 low-risk thymomas) were finally included. Visual findings of PET visual grade (P < 0.001) and PET central metabolic defect (P < 0.001) showed significant differences between thymic cysts and low-risk thymomas, but CT shape did not. Among the quantitative parameters, PET SUVmax (P < 0.001), CT diameter (P < 0.001), and CT HU (P = 0.004) showed significant differences. In ROC analysis, PET SUVmax demonstrated the highest area under the curve (AUC) of 0.996 (P < 0.001), with a cut-off of equal to or less than 2.1 having a sensitivity of 100.0% and specificity of 94.2%. The AUC of PET SUVmax was significantly larger than that of CT diameter (P = 0.009) and CT HU (P = 0.004). CONCLUSIONS: Among the [18F]FDG PET/CT parameters examined, low FDG uptake (SUVmax ≤ 2.1, equal to or less than the mediastinum) is a strong diagnostic marker for a thymic cyst. PET visual grade and central metabolic defect are easily accessible findings.

Diagnostic Efficacy Study Comparing Tzanakis Scoring System With Alvarado Scoring System in Effective Diagnosis of Acute Appendicitis.

Objective Among the common causes of abdominal emergencies, acute appendicitis ranks at the top, particularly in the young population. While negative appendectomy is not uncommon, the risk of appendicular perforation is substantial if the diagnosis is missed or delayed. This study evaluated the diagnostic efficacy of the Tzanakis scoring system for acute appendicitis, comparing it with the Alvarado scoring system, considering the histopathological finding as the gold standard. Materials and methods This prospective observational study, conducted in the General Surgery department in a tertiary care hospital in India, included clinically diagnosed acute appendicitis cases posted for open or laparoscopic appendicectomy. Results The mean age for the 60 participants included in the study was 30.97±13.44, and the median was 24.5 yrs. The sensitivity of ultrasonography (USG) in diagnosing histopathological positive acute appendicitis was 89%, and the specificity was 50%. The sensitivity, specificity, positive, and negative predictive values of the Tzanakis score were 87%, 50%, 96%, and 22%, respectively, and those of the Alvarado score were 54%, 75%, 96%, and 10%, respectively. Conclusion The receiver operator characteristic (ROC) curve for the Alvarado and Tzanakis scores showed that the area under the curve (AUC) was greater for the Tzanakis scoring system (0.670) than for the Alvarado scoring system (0.598). Differences between the AUCs were not statistically significant. Although the Tzanakis scoring system is more sensitive than the Alvarado scoring system in diagnosing acute appendicitis, studies with larger samples are needed to show the superiority of this scoring system over the Alvarado scoring system.

Malnutrition screening tool and nutritional screening tool for classification of nutritional risk in patients with cancer upon hospital admission: Comparison of diagnostic performance using Global Leadership Initiative on malnutrition criteria as reference.

BACKGROUND & AIMS: Tools for screening of nutrition risk in patients with cancer are usually validated against other screening instruments. Here with the performance of Malnutrition Screening Tool (MST) and Nutritional Screening Tool (NUTRISCORE) to identify the risk of malnutrition was assessed. A full nutritional evaluation and diagnosis following criteria from the Global Leadership Initiative of Malnutrition (GLIM) was the reference standard for the classification of malnutrition. METHODS: Diagnostic test prospective analysis of adult patients with a confirmed diagnosis of cancer. MST, NUTRISCORE and nutritional evaluation and diagnosis by GLIM criteria were independently performed within 24 h of admission to a 4th tier hospital in Bogotá, Colombia. RESULTS: From 439 patients the sensitivity and specificity of MST was 75% and 94% and of NUTRISCORE 45% and 97% respectively. The area under receiver operating characteristic (ROC) curves were 0.90 for MST and 0.85 for NUTRISCORE (p = 0.003). CONCLUSION: The MST showed a significantly better diagnostic performance over NUTRISCORE for detection of malnutrition risk at admission to hospital of patients with cancer.

Urinary methotrexate dosage in rheumatoid arthritis, in patients treated for at least 6 months: a potential marker of adherence.

OBJECTIVES: Non-adherence to rheumatoid arthritis (RA) treatments must be identified. A methotrexate (MTX) urinary dosage (METU) was recently developed. The aim of our study was to assess adherence to MTX in RA using METU in real-life conditions and to compare it with indirect adherence measurement technics. METHODS: We performed a cross-sectional study at Reims University Hospital. We included over 18-year-old patients with RA treated by MTX for more than 6 months. Patients were invited to complete demographic, clinical and psychological questionnaires and adherence measurement technics (Compliance Questionnaire of Rheumatology (CQR) and Medication Possession Ratio (MPR)). A urinary sample was collected to measure MTX and information about tolerance was evaluated through Methotrexate Intolerance Severity Score. RESULTS: 84 patients were included, 26 using oral MTX, 58 subcutaneous (SC) MTX. Among them, 73% were female, mean age was 61.5 years, MTX mean dose was 15 mg/week and 61.9% were treated by biological DMARDs (Disease Modifying Antirheumatic Drugs). 77 patients (91.7%) were adherent to treatment according to METU, whereas MPR and CQR reported less adherence (69.5% and 61.9%, respectively). MPR and METU were not significantly different in SC MTX users (p=0.059). Non-adherent patients had a higher number of tender joints and C reactive protein value (p<0.05). CONCLUSION: This is the first largest study evaluating MTX adherence in patients with RA using a urinary dosage. We identified that indirect adherence measurements did not reflect real-life adherence. It would be appreciable to realise METU, in a new study, in patients with RA with unexplained response to treatment, to consider it before escalating therapeutic strategy.

Comparison of the Prognostic Accuracy of Full Outline of Unresponsiveness (FOUR) Score with Glasgow Coma Scale (GCS) Score among Patients with Traumatic Brain Injury in a Tertiary Care Center.

Objectives The Glasgow Coma Scale (GCS) is widely used and considered the gold standard in assessing the consciousness of patients with traumatic brain injury. However, some significant limitations, like the considerable variations in interobserver reliability and predictive validity, were the reason for developing the Full Outline of Unresponsiveness (FOUR) score. The current study aims to compare the prognostic accuracy of the FOUR score with the GCS score for in-hospital mortality and morbidity among patients with traumatic brain injury. Materials and Methods A prospective cohort study was conducted, where 237 participants were selected by consecutive sampling from a tertiary care center. These patients were assessed with the help of GCS and FOUR scores within 6 hours of admission, and other clinical parameters were also noted. The level of consciousness was checked every day with the help of GCS and FOUR scores until their last hospitalization day. Glasgow Outcome Scale was used to assess their outcome on the last day of hospitalization. The GCS and FOUR scores were compared, and data were analyzed by descriptive and inferential statistics. The chi-square test, independent Student's t -test, and receiver operating characteristic analysis were used for inferential analysis. Results The area under the curve (AUC) for the GCS score at the 6th hour for predicting mortality was 0.865 with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 64%. The AUC for FOUR scores at the 6th hour for predicting the mortality was 0.893, with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 73%. Conclusion The current study shows that, as per the AUC of GCS and FOUR scores, their sensitivity was equal, but specificity was higher in the FOUR score. So, the FOUR score has higher accuracy than the GCS score in the prediction of mortality among traumatic brain injury patients.

Exploring complement biomarkers in suspected axial spondyloarthritis.

OBJECTIVES: To investigate lectin pathway proteins (LPPs) as biomarkers for axial spondyloarthritis (axSpA) in a cross-sectional cohort with a suspicion of axSpA, comprising newly diagnosed axSpA and chronic low back pain (cLBP) individuals. METHODS: Serum samples from 515 participants within the OptiRef cohort, including 151 axSpA patients and 364 cLBP patients, were measured using immunoassays for LPPs (mannan-binding lectin (MBL), collectin liver-1 (CL-L1), M-ficolin, H-ficolin and L-ficolin, MBL-associated serine proteases (MASP)-1, -2 and -3, MBL-associated proteins (MAp19 and MAp44) and the complement activation product C3dg). RESULTS: Serum levels of L-ficolin, MASP-2 and C3dg were elevated in axSpA patients, whereas levels of MASP-3 and CL-L1 were decreased, and this remained significant for C3dg and MASP-3 after adjustment for C reactive protein (CRP). A univariate regression analysis showed serum levels of CL-L1, MASP-2, MASP-3 and C3dg to predict the diagnosis of axSpA, and MASP-3 and C3dg remained significant in a multivariate logistic regression analysis. Assessment of the diagnostic potential showed that a combination of human leukocyte antigen B27 (HLA-B27) and measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, however, with a concomitant loss of sensitivity. CONCLUSIONS: Serum levels of complement activation, that is, C3dg, and MASP-3 differed significantly between axSpA and cLBP patients after adjustment for CRP. Although combining HLA-B27 with measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, this seems unjustified due to the concomitant loss of sensitivity. However, both C3dg and MASP-3 were associated with axSpA diagnosis in multivariate logistic regression, suggesting an involvement of complement in the inflammatory processes and possibly pathogenesis in axSpA.

Performance of the first-trimester Fetal Medicine Foundation competing risks model for preeclampsia prediction: an external validation study in Brazil.

BACKGROUND: The current version of the Fetal Medicine Foundation competing risks model for preeclampsia prediction has not been previously validated in Brazil. OBJECTIVE: This study aimed (1) to validate the Fetal Medicine Foundation combined algorithm for the prediction of preterm preeclampsia in the Brazilian population and (2) to describe the accuracy and calibration of the Fetal Medicine Foundation algorithm when considering the prophylactic use of aspirin by clinical criteria. STUDY DESIGN: This was a cohort study, including consecutive singleton pregnancies undergoing preeclampsia screening at 11 to 14 weeks of gestation, examining maternal characteristics, medical history, and biophysical markers between October 2010 and December 2018 in a university hospital in Brazil. Risks were calculated using the 2018 version of the algorithm available on the Fetal Medicine Foundation website, and cases were classified as low or high risk using a cutoff of 1/100 to evaluate predictive performance. Expected and observed cases with preeclampsia according to the Fetal Medicine Foundation-estimated risk range (≥1 in 10; 1 in 11 to 1 in 50; 1 in 51 to 1 in 100; 1 in 101 to 1 in 150; and <1 in 150) were compared. After identifying high-risk pregnant women who used aspirin, the treatment effect of 62% reduction in preterm preeclampsia identified in the Combined Multimarker Screening and Randomized Patient Treatment with Aspirin for Evidence-Based Preeclampsia Prevention trial was used to evaluate the predictive performance adjusted for the effect of aspirin. The number of potentially unpreventable cases in the group without aspirin use was estimated. RESULTS: Among 2749 pregnancies, preterm preeclampsia occurred in 84 (3.1%). With a risk cutoff of 1/100, the screen-positive rate was 25.8%. The detection rate was 71.4%, with a false positive rate of 24.4%. The area under the curve was 0.818 (95% confidence interval, 0.773-0.863). In the risk range ≥1/10, there is an agreement between the number of expected cases and the number of observed cases, and in the other ranges, the predicted risk was lower than the observed rates. Accounting for the effect of aspirin resulted in an increase in detection rate and positive predictive values and a slight decrease in the false positive rate. With 27 cases of preterm preeclampsia in the high-risk group without aspirin use, we estimated that 16 of these cases of preterm preeclampsia would have been avoided if this group had received prophylaxis. CONCLUSION: In a high-prevalence setting, the Fetal Medicine Foundation algorithm can identify women who are more likely to develop preterm preeclampsia. Not accounting for the effect of aspirin underestimates the screening performance.

Value of turbo spin echo-based diffusion-weighted imaging in the differential diagnosis of benign and malignant solitary pulmonary lesions.

To quantitatively assess the diagnostic efficacy of multiple parameters derived from multi-b-value diffusion-weighted imaging (DWI) using turbo spin echo (TSE)-based acquisition techniques in patients with solitary pulmonary lesions (SPLs). A total of 105 patients with SPLs underwent lung DWI using single-shot TSE-based acquisition techniques and multiple b values. The apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters, and lesion-to-spinal cord signal intensity ratio (LSR), were analyzed to compare the benign and malignant groups using the Mann-Whitney U test and receiver operating characteristic analysis. The Dstar values observed in lung cancer were slightly lower than those observed in pulmonary benign lesions (28.164 ± 31.950 versus 32.917 ± 34.184; Z = -2.239, p = 0.025). The LSR values were significantly higher in lung cancer than in benign lesions (1.137 ± 0.581 versus 0.614 ± 0.442; Z = - 4.522, p < 0.001). Additionally, the ADC800, ADCtotal, and D values were all significantly lower in lung cancer than in the benign lesions (Z = - 5.054, -5.370, and -6.047, respectively, all p < 0.001), whereas the f values did not exhibit any statistically significant difference between the two groups. D had the highest area under the curve (AUC = 0.887), followed by ADCtotal (AUC = 0.844), ADC800 (AUC = 0.824), and LSR (AUC = 0.789). The LSR, ADC800, ADCtotal, and D values did not differ statistically significantly in diagnostic effectiveness. Lung DWI using TSE is feasible for differentiating SPLs. The LSR method, conventional DWI, and IVIM have comparable diagnostic efficacy for assessing SPLs.

Beneath the surface: A systematic review on intraoperative imaging techniques for deep margin assessment in oral squamous cell carcinoma.

Resection margins of oral squamous cell carcinoma (SCC) are often inadequate. A systematic review on clinical intraoperative whole-specimen imaging techniques to obtain adequate deep resection margins in oral SCC is lacking. Such a review may render better alternatives for the current insufficient intraoperative techniques: palpation and frozen section analyses (FSA). This review resulted in ten publications investigating ultrasound (US), four investigating fluorescence, and three investigating MRI. Both US and fluorescence were able to image the tumor intraorally and perform ex-vivo imaging of the resection specimen. Fluorescence was also able to image residual tumor tissue in the wound bed. MRI could only be used on the ex-vivo specimen. The 95 % confidence intervals for sensitivity and specificity were large, due to the small sample sizes for all three techniques. The sensitivity and specificity of US for identifying < 5 mm margins ranged from 0 % to 100 % and 60 % to 100 %, respectively. For fluorescence, this ranged from 0 % to 100 % and 76 % to 100 %, respectively. For MRI, this ranged from 7 % to 100 % and 81 % to 100 %, respectively. US, MRI and fluorescence are the currently available imaging techniques that can potentially be used intraoperatively and which can image the entire tumor-free margin, although they have insufficient sensitivity for identifying < 5 mm margins. Further research on larger cohorts is needed to improve the sensitivity by determining cut-off points on imaging for inadequate margins. This improves the number of adequate resections of oral SCC's and pave the way for routine clinical implementation of these techniques.

Predictive validity of the Developmental Coordination Disorder Questionnaire as a screening tool to identify motor skill problems: A systematic review and meta-analysis.

BACKGROUND: The Developmental Coordination Disorder Questionnaire (DCDQ) has been used to screen children who probably have developmental coordination disorder (DCD). AIMS: We systematically reviewed studies on the predictive validity of the DCDQ and performed a meta-analysis on its diagnostic accuracy. METHODS AND PROCEDURES: Literature was searched through four electronic databases: MEDLINE, Embase, CINAHL, and PsycArticles. A total of 27 studies was selected based on the inclusion criteria. The sensitivity and specificity of the DCDQ were assessed using summary receiver operating characteristic (sROC) curves. Subgroup analyses were conducted according to the DCDQ type, reference standard, and participant type. OUTCOMES AND RESULTS: Overall, the DCDQ has a sensitivity of 0.70 and a specificity of 0.77, showing moderate diagnostic accuracy (area under the curve, 0.80). Subgroup analysis showed that the revised version of the DCDQ had higher diagnostic accuracy than the original version. When the reference standard was the Diagnostic and Statistical Manual of Mental Disorders, the sensitivity and specificity of the DCDQ were 0.87 and 0.83, respectively. The diagnostic accuracy was higher in clinical samples compared to the general population. CONCLUSIONS AND IMPLICATIONS: This study demonstrated that the DCDQ has adequate diagnostic accuracy, suggesting it can help screen children with motor skill deficits.

[Importance of aspirin challenges in patients with NSAID-exacerbated respiratory disease]. / Stellenwert von ASS-Provokationen beim Analgetika-Intoleranz-Syndrom.

BACKGROUND: Nonsteroidal anti-inflammatory drug-exacerbated respiratory disease (N-ERD) is often characterized by a severe course of chronic rhinosinusitis with nasal polyps (CRSwNP), comorbid asthma, and NSAID hypersensitivity. The gold standard for N-ERD diagnosis is challenge with acetylsalicylic acid (ASA). In expert recommendations, the diagnosis of N-ERD is established based on a plausible positive history of NSAID hypersensitivity and CRSwNP with asthma. OBJECTIVE: The following review describes the performance of ASA challenges and their sensitivity and specificity. It also examines the extent to which a positive history of NSAID hypersensitivity correlates with ASA challenge results in clinical trials and when ASA challenges should be performed. RESULTS AND CONCLUSION: ASA challenges have high sensitivity and specificity. In clinical ASA challenge studies, there is a high concordance between a positive history of NSAID hypersensitivity obtained by rhinologists and the measured data of ASA challenge in patients with CRSwNP and comorbid asthma. Therefore, ASA challenge is primarily indicated in patients with an unclear history of NSAID hypersensitivity.

¿Cómo detectar a los pacientes mayores no institucionalizados en riesgo de malnutrición durante su hospitalización? Comparación de 8 herramientas de cribado de malnutrición o de riesgo nutricional / How to detect non-institutionalized older patients at risk of malnutrition during their hospitalization? Comparison of 8 screening tools for malnutrition or nutritional risk

Antecedentes: La prevalencia de malnutrición es elevada entre la población mayor. El ingreso hospitalario es una ventana de oportunidad para su detección. Objetivo: Valorar la concordancia de distintas escalas nutricionales en pacientes hospitalizados.Método: Estudio prospectivo en pacientes mayores de 65años no institucionalizados ingresados en un servicio de Medicina Interna. Se compararon 5 encuestas de cribado de malnutrición (MNA, MST, MUST, NRS-2000 y CONUT) y 3 encuestas de cribado de riesgo nutricional (SCREEN3, 8 y 14). Como patrón de referencia se utilizó la definición de malnutrición de la Iniciativa Global para el Liderazgo en Malnutrición (GLIM). Resultados: Se incluyeron 85 pacientes (37% mujeres, mediana de edad 83años). El 48% (IC95%: 38-59%) de los pacientes fueron clasificados como malnutridos según criterios GLIM. La escala SCREEN3 fue la más sensible (93%; IC95%: 87-98) y MUST la más específica (91%; IC95%: 85-99). La escala más eficaz para excluir la sospecha de malnutrición fue SCREEN3 (LR− 0,17; IC95%: 0,05-0,53) y la mejor para confirmarla fue MST (LR+ 7,08; IC95%: 3,06-16,39). La concordancia entre las distintas escalas fue baja o muy baja, con índices kappa entre 0,082 y 0,465.Conclusiones: Se precisa un abordaje integral para detectar la malnutrición en adultos mayores ingresados. Las escalas más sensibles son más útiles en el cribado inicial. Las herramientas de riesgo nutricional podrían ser eficaces en esta etapa. En un segundo paso se debe confirmar la malnutrición de acuerdo con criterios establecidos como los de la GLIM.(AU)

Background: The prevalence of malnutrition is high among the elderly population. Hospital admission is a window of opportunity for its detection. Objective: To assess the concordance of different nutritional scales in hospitalized patients. Methods: Prospective study in non-institutionalized patients over 65years of age admitted to an internal medicine department. Five malnutrition screening surveys (MNA, MST, MUST, NRS-2000 and CONUT) and three nutritional risk screening surveys (SCREEN3, 8 and 14) were compared. As gold standard we use the Global Leadership Initiative for Malnutrition (GLIM) definition of malnutrition. Results: Eighty-five patients (37% female, median age 83years) were included. Forty-eight percent (95%CI: 38-59%) of patients were classified as malnourished according to GLIM criteria. The SCREEN3 scale was the most sensitive (93%; 95%CI: 87-98) and MUST the most specific (91%; 95%CI: 85-99). The most effective scale for excluding suspected malnutrition was SCREEN3 (LR− 0.17; 95%CI: 0.05-0.53) and the best for confirming it was MST (LR+ 7.08; 95%CI: 3.06-16.39). Concordance between the different scales was low or very low with kappa indices between 0.082 and 0.465. Conclusions: A comprehensive approach is needed to detect malnutrition in hospitalized patients. More sensitive scales are more useful in initial screening. Nutritional risk tools could be effective at this stage. In a second step, malnutrition should be confirmed according to established criteria such as GLIM.(AU)